########################################################################
##
##  Purpose: This script produces Figure 1 from the manuscript
##  Author: james.h.bisbee@vanderbilt.edu
##  Date: 05/18/2024
##
##  Input Files:
##    - ./data/for_replication.rds
##  Output Files:
##    - ./output/Figures/MUSK_fig1.pdf
##
########################################################################

rm(list = ls())
gc()

require(changepoint)
require(tidyverse)
require(ggridges)
require(patchwork)

# Compute details
Sys.info()
# sysname        release        version       nodename 
# "Windows"       "10 x64"  "build 22631"   "AS-GR3RGY3" 
# machine          login           user effective_user 
# "x86-64"     "bisbeejh"     "bisbeejh"     "bisbeejh"

ram_size = system("wmic MemoryChip get Capacity", intern = TRUE)[-1]
model_name = system("wmic cpu get name", intern = TRUE)[2] # nocov
vendor_id = system("wmic cpu get manufacturer", intern = TRUE)[2] # nocov

print(list(ram = stringr::str_squish(ram_size)[1],
           vendor_id = stringr::str_squish(vendor_id),
           model_name = stringr::str_squish(model_name),
           no_of_cores = parallel::detectCores()))

# $ram
# [1] "17179869184"
# 
# $vendor_id
# [1] "GenuineIntel"
# 
# $model_name
# [1] "13th Gen Intel(R) Core(TM) i9-13900H"
# 
# $no_of_cores
# [1] 20

# Package details
sessionInfo()

# attached base packages:
# [1] stats     graphics  grDevices utils     datasets 
# [6] methods   base     
# 
# other attached packages:
#  [1] patchwork_1.1.3   ggridges_0.5.4    lubridate_1.9.2  
#  [4] forcats_1.0.0     stringr_1.5.0     dplyr_1.1.2      
#  [7] purrr_1.0.1       readr_2.1.4       tidyr_1.3.0      
# [10] tibble_3.2.1      ggplot2_3.4.4     tidyverse_2.0.0  
# [13] changepoint_2.2.4 zoo_1.8-12       
# 
# loaded via a namespace (and not attached):
#  [1] vctrs_0.6.3       cli_3.6.1         rlang_1.1.1      
#  [4] stringi_1.7.12    generics_0.1.3    glue_1.6.2       
#  [7] colorspace_2.1-0  hms_1.1.3         scales_1.3.0     
# [10] fansi_1.0.4       grid_4.3.3        munsell_0.5.0    
# [13] tzdb_0.4.0        lifecycle_1.0.3   compiler_4.3.3   
# [16] timechange_0.2.0  pkgconfig_2.0.3   rstudioapi_0.15.0
# [19] lattice_0.22-5    R6_2.5.1          tidyselect_1.2.0 
# [22] utf8_1.2.3        pillar_1.9.0      magrittr_2.0.3   
# [25] tools_4.3.3       withr_2.5.0       gtable_0.3.3

finalFullUsers <- read_rds('./data/for_replication.rds')

toplot <- finalFullUsers %>%
  group_by(created_at) %>%
  summarise(nTweets = sum(nTweets,na.rm=T),
            nAccounts = length(unique(sn))) %>%
  gather(metric,value,-created_at)

# Left Facet
pAccounts <- toplot %>%
  filter(metric == 'nAccounts') %>%
  mutate(metric = ifelse(metric == 'nAccounts','# Active Accounts','# Tweets')) %>%
  ggplot(aes(x = created_at,y = value)) +
  geom_point() +
  geom_vline(xintercept = as.Date('2022-10-28'),linetype = 'dashed',size = 1.1,color = 'red') + 
  annotate(geom = 'label',x = as.Date('2022-10-28'),y = Inf,label = 'Musk',vjust = 1,hjust = .5) + 
  
  facet_wrap(~metric,scales = 'free_y') + 
  theme_bw() + 
  labs(x = 'Date',
       y = 'Number of accounts')

# Right Facet
pTweets <- toplot %>%
  filter(metric == 'nTweets') %>%
  mutate(metric = ifelse(metric == 'nAccounts','# Active Accounts','# Tweets')) %>%
  ggplot(aes(x = created_at,y = value)) +
  geom_point() +
  geom_vline(xintercept = as.Date('2022-10-28'),linetype = 'dashed',size = 1.1,color = 'red') + 
  annotate(geom = 'label',x = as.Date('2022-10-28'),y = Inf,label = 'Musk',vjust = 1,hjust = .5) + 
  facet_wrap(~metric,scales = 'free_y') + 
  theme_bw() + 
  labs(x = 'Date',
       y = 'Number of tweets')


pdf('./output/Figures/MUSK_fig1.pdf',width = 7,height = 3)
pAccounts + pTweets
dev.off()

# EOF